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More with less: Lowering user burden in mobile crowdsourcing through compressive sensing

Xu, L; Hao, X; Lane, ND; Liu, X; Moscibroda, T; (2015) More with less: Lowering user burden in mobile crowdsourcing through compressive sensing. In: Miyahara, H and Tokuda, H and Mase, K and Langheinrich, M, (eds.) Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing. (pp. pp. 659-670). Association for Computing Machinery: Osaka, Japan. Green open access

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Abstract

Mobile crowdsourcing is a powerful tool for collecting data of various types. The primary bottleneck in such systems is the high burden placed on the user who must manually collect sensor data or respond in-situ to simple queries (e.g., experience sampling studies). In this work, we present Compressive CrowdSensing (CCS) - a framework that enables compressive sensing techniques to be applied to mobile crowdsourcing scenarios. CCS enables each user to provide significantly reduced amounts of manually collected data, while still maintaining acceptable levels of overall accuracy for the target crowd-based system. Näive applications of compressive sensing do not work well for common types of crowdsourcing data (e.g., user survey responses) because the necessary correlations that are exploited by a sparsifying base are hidden and non-Trivial to identify. CCS comprises a series of novel techniques that enable such challenges to be overcome. We evaluate CCS with four representative large-scale datasets and find that it is able to outperform standard uses of compressive sensing, as well as conventional approaches to lowering the quantity of user data needed by crowd systems.

Type: Proceedings paper
Title: More with less: Lowering user burden in mobile crowdsourcing through compressive sensing
Event: UbiComp '15 : ACM International Joint Conference on Pervasive and Ubiquitous Computing, Osaka, Japan, September 07 - 11, 2015
ISBN-13: 9781450335744
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/2750858.2807523
Publisher version: http://dx.doi.org/10.1145/2750858.2807523
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Compressive sensing, mobile crowdsensing.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1503677
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